mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-08-04 02:37:44 +00:00
Xu Yang
90d9cdd0e9
* udpate plot * log and reduce token * trace tag * add simple_background parameter to get_scenario_all_desc * update trace * update first version code * chat model map * add annotation for stack index * add annotation * reformatted by black * several update on kaggle scenarios * update some new change * fix CI * fix CI * fix a bug * fix bugs in graph RAG --------- Co-authored-by: Tim <illking@foxmail.com>
73 lines
2.4 KiB
Python
73 lines
2.4 KiB
Python
from copy import deepcopy
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from pathlib import Path
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from rdagent.components.coder.model_coder.model import (
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ModelExperiment,
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ModelFBWorkspace,
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ModelTask,
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)
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from rdagent.core.experiment import Task
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from rdagent.core.prompts import Prompts
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from rdagent.core.scenario import Scenario
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from rdagent.scenarios.qlib.experiment.workspace import QlibFBWorkspace
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prompt_dict = Prompts(file_path=Path(__file__).parent / "prompts.yaml")
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class QlibModelExperiment(ModelExperiment[ModelTask, QlibFBWorkspace, ModelFBWorkspace]):
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def __init__(self, *args, **kwargs) -> None:
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super().__init__(*args, **kwargs)
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self.experiment_workspace = QlibFBWorkspace(template_folder_path=Path(__file__).parent / "model_template")
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class QlibModelScenario(Scenario):
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def __init__(self) -> None:
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super().__init__()
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self._background = deepcopy(prompt_dict["qlib_model_background"])
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self._output_format = deepcopy(prompt_dict["qlib_model_output_format"])
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self._interface = deepcopy(prompt_dict["qlib_model_interface"])
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self._simulator = deepcopy(prompt_dict["qlib_model_simulator"])
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self._rich_style_description = deepcopy(prompt_dict["qlib_model_rich_style_description"])
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self._experiment_setting = deepcopy(prompt_dict["qlib_model_experiment_setting"])
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@property
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def background(self) -> str:
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return self._background
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@property
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def source_data(self) -> str:
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raise NotImplementedError("source_data of QlibModelScenario is not implemented")
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@property
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def output_format(self) -> str:
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return self._output_format
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@property
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def interface(self) -> str:
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return self._interface
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@property
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def simulator(self) -> str:
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return self._simulator
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@property
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def rich_style_description(self) -> str:
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return self._rich_style_description
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@property
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def experiment_setting(self) -> str:
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return self._experiment_setting
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def get_scenario_all_desc(
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self, task: Task | None = None, filtered_tag: str | None = None, simple_background: bool | None = None
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) -> str:
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return f"""Background of the scenario:
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{self.background}
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The interface you should follow to write the runnable code:
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{self.interface}
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The output of your code should be in the format:
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{self.output_format}
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The simulator user can use to test your model:
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{self.simulator}
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"""
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